All reconstruction hyperparameters for the three methods were tuned on the validation set and held fixed on the test set. Normalized root mean squared error (NRMSE) was used to evaluate the performance of the methods.
Our algorithm was implemented in PyTorch and gradients for \(\kappa _t\)  in Eq. () were calculated through auto-differentiation. Inference was run on one Nvidia RTX 3090.
As all training, validation, and test data was taken from a publicly available dataset [1]} and motion was retrospectively simulated, ethical approval was not required.
